What makes OpenJet a self-hosted LLM solution?

OpenJet runs the model and the operating interface locally on your own hardware, rather than sending prompts and evidence to a managed API.

How is this different from a generic self-hosted chat UI?

OpenJet is aimed at operational workflows: local logs, local scripts, local approval, and local execution close to the system being managed.

Should OpenJet be used to let the model write new code on mission-critical hardware?

No. The better pattern is to let OpenJet help the human find the right script or procedure, then require approval before anything state-changing runs.

self hosted llm

Self-hosted LLM for controlled local execution

Deploy the model, tool runtime, and operator workflow on infrastructure you control.

OpenJet gives teams a self-hosted LLM interface that runs near the hardware it serves. The model is local, the tool runtime is local, and the operator stays in control of state-changing actions.

Install OpenJet Read the docs

Why local wins

Self-hosted by design. Run local GGUF and hardware-optimized backends on Jetson and Linux systems without routing prompts to a hosted API.
Operator remains in control. OpenJet is structured around approved execution, which is a better pattern for sensitive systems than letting an LLM act unchecked.
Best as a wrapper over trusted scripts. The strongest pattern is to use natural language to find the right evidence and run pre-verified procedures already staged on the device.
Available to your own code. A Python SDK exposes the same self-hosted runtime as an inference session, so internal services can call the local model directly instead of going through an operator's terminal.

Common deployment paths

Deploy a self-hosted LLM on your own Jetson or Linux hardware instead of relying on a hosted API.
Give operators a local AI interface without allowing free-form code generation on critical systems.
Use natural language to surface and run trusted operational scripts under human approval.
Call the self-hosted model from your own Python services with the OpenJet SDK.

Frequently asked questions

What makes OpenJet a self-hosted LLM solution?: OpenJet runs the model and the operating interface locally on your own hardware, rather than sending prompts and evidence to a managed API.
How is this different from a generic self-hosted chat UI?: OpenJet is aimed at operational workflows: local logs, local scripts, local approval, and local execution close to the system being managed.
Should OpenJet be used to let the model write new code on mission-critical hardware?: No. The better pattern is to let OpenJet help the human find the right script or procedure, then require approval before anything state-changing runs.

Explore OpenJet

Embed a local model with the Python SDK, run Qwen3.8-27B as a local coding agent, compare local coding-agent alternatives, read the docs, or go back to the homepage.